Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Regional Image Reconstruction with Optimum Currents for MREIT - Evaluation on Shepp-Logan Conductivity Phantom
Date
2008-11-27
Author
Eyüboğlu, Behçet Murat
Altunel, Haluk
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
155
views
0
downloads
Cite This
In this study, an image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT) is proposed to achieve maximum benefit of optimum current injection patterns. By doing so, considerable reduction in probing current amplitude could be possible. In the proposed algorithm, field of view (FOV) is divided into a number of segments. Image of each segment is reconstructed separately, based on measurements obtained using the best (optimum) current patterns, which maximize distinguishability for the same segment. Images reconstructed individually for all segments are then merged to form an image of the entire FOV. The proposed regional image reconstruction (RIR) algorithm is evaluated with simulated measurements obtained from a conductivity phantom having Shepp-Logan head phantom geometry. Smaller reconstruction errors and perceptively better images are obtained by using RIR instead of conventional reconstruction (CR). Improvement is more significant for small inhomogeneities which are away from the outer surface. When SNR is 13 dB, conductivity error for small inhomogeneities reconstructed by RIR is almost half of the errors of CR.
Subject Keywords
Magnetic resonance electrical impedance tomography
,
Imaging
,
Optimum currents
,
Distinguishability
URI
https://hdl.handle.net/11511/54092
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Equipotential projection based magnetic resonance electrical impedance tomography (mr-eit) for high resolution conductivity imaging
Özdemir, Mahir Sinan; Eyüboğlu, Behçet Murat; Department of Electrical and Electronics Engineering (2003)
In this study, a direct reconstruction algorithm for Magnetic Resonance Electrical Impedance Tomography (MR-EIT) is proposed and experimentally implemented for high resolution true conductivity imaging. In MR-EIT, elec trical impedance tomography (EIT) and magnetic resonance imaging (MRI) are combined together. Current density measurements are obtained making use of Magnetic Resonance Current Density Imaging (MR-CDI) techniques and peripheral potential measurements are determined using conventional EIT tech...
Magnetic Resonance - Electrical Impedance Tomography (MR-EIT) Research at METU
Eyüboğlu, Behçet Murat (2006-09-01)
Following development of magnetic resonance current density imaging (MRCDI), magnetic resonance - electrical impedance tomography (MR-EIT) has emerged as a promising approach to produce high resolution conductivity images. Electric current applied to a conductor results in a potential field and a magnetic flux density distribution. Using a magnetic resonance imaging (MRI) system, the magnetic flux density distribution can be reconstructed as in MRCDI. The flux density is related to the current density distr...
Equipotential projection based MREIT reconstruction without potential measurements
Eyüboğlu, Behçet Murat (2007-09-02)
Magnetic resonance electrical impedance tomography (MREIT) is used to produce high resolution images of true conductivitv distribution. Images are reconstructed by utilising measurements of magnetic flux density distribution and surface potentials. Surface potential measurements are needed to reconstruct true conductivity values. In this study, a novel MREIT reconstruction algorithm is developed to generate conductivity images without utilizing the surface potential measurements. The proposed algorithm and ...
Image Reconstruction in Magnetic Resonance Conductivity Tensor Imaging (MRCTI)
DEĞİRMENCİ, EVREN; Eyüboğlu, Behçet Murat (2012-03-01)
Almost all magnetic resonance electrical impedance tomography (MREIT) reconstruction algorithms proposed to date assume isotropic conductivity in order to simplify the image reconstruction. However, it is well known that most of biological tissues have anisotropic conductivity values. In this study, four novel anisotropic conductivity reconstruction algorithms are proposed to reconstruct high resolution conductivity tensor images. Performances of these four algorithms and a previously proposed algorithm are...
Imaging anisotropic conductivity with induced current magnetic resonance electrical impedance tomography (ICMREIT)
Eroğlu, Hasan Hüseyin; Sadighi, Mehdi; Eyüboğlu, Behçet Murat (2018-06-27)
In gradient coil based induced current magnetic resonance electrical impedance tomography (ICMREIT), gradient coils of a conventional magnetic resonance imaging (MRI) scanner are excited with time varying waveforms embedded in an MRI pulse sequence [1], [2], [3]. As a result of the excitation, low frequency (LF) eddy current is induced in the volume conductor media being imaged which accumulates phase to MR signal. By measuring and post-processing the LF phase of the eddy current, LF conductivity images are...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. M. Eyüboğlu and H. Altunel, “Regional Image Reconstruction with Optimum Currents for MREIT - Evaluation on Shepp-Logan Conductivity Phantom,” 2008, vol. 22, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54092.
